Construction of Gene Interaction Network with Computational Life

通过构建具有计算生命的基因相互作用网络，得到了以下结果：针对基因相互作用网络模型，提出了一种基因功能标注方法。本研究以RIKEN基因组科学中心测序的小鼠全长cDNA序列为研究对象，对其序列相似性进行聚类，探索共同保守区域的候选序列，并通过去除Inter Pro等已知数据库中的基序获得16个新的候选基序。通过与已知基因序列的同源性、染色体的位置、蛋白质二级结构和跨膜区域的预测等分析，对10个候选基序进行了功能注释。为小鼠cDNA微阵列开发了小鼠不同发育阶段和组织的基因表达谱数据库，该数据库由RIKEN基因组科学中心开发。通过基因表达谱聚类分析，揭示了与发育阶段、组织特异性和代谢途径相关的一系列基因。虽然许多研究人员已经用微阵列数据完成了一组基因的功能预测，但通过FANTOM联盟的可靠注释，可以阐明给定基因的功能关系和发现未知功能的基因。

The following results were obtained by the construction of gene interaction network with computational life. For the model of gene interaction network, a method was developed for the functional annotation of genes. As the target of our research, the mouse full-length cDNA sequences, which were sequenced by RIKEN Genome Science Center, were clustered with their sequence similarity, the candidates for commonly conserved regions were explored, and 16 new motif candidates were obtained by removing the motifs found in known databases such as Inter Pro. Ten of the detected motif candidates were functionally annotated by various analyses, such as homology to the known gene sequences, the location of chromosomes, the predictions of protein secondary structure and transmembrane regions.Databases for expression profiles of the mouse genes at various developmental phases and tissues were developedfor the mouse cDNA microarray, which were developed at RIKEN Genome Science Center. A set of genes related to developmental phases, tissue specificity and metabolic pathway were elucidated by the clustering of gene expression profiles. Although many researchers have already done the functional predictions of a set of genes with microarray data, the elucidation of functional relationships of given genes and the gene finding with unknown functions became able to do using reliable annotations by the FANTOM consortium.